1 files changed, 29 insertions, 27 deletions
diff --git a/macros/arch_test.sci b/macros/arch_test.sci
index 5cb8ed8..9a1d4a5 100644
--- a/macros/arch_test.sci
+++ b/macros/arch_test.sci
@@ -1,36 +1,38 @@
-/*
-Description:
-            Perform a Lagrange Multiplier (LM) test for conditional heteroscedasticity.
-            For a linear regression model
-            y = x * b + e
-            perform a Lagrange Multiplier (LM) test of the null hypothesis of no conditional heteroscedascity against the alternative of CH(p).
-            I.e., the model is
-            y(t) = b(1) * x(t,1) + … + b(k) * x(t,k) + e(t),
-            given y up to t-1 and x up to t, e(t) is N(0, h(t)) with
-            h(t) = v + a(1) * e(t-1)^2 + … + a(p) * e(t-p)^2,
-            and the null is a(1) == … == a(p) == 0.
-            If the second argument is a scalar integer, k, perform the same test in a linear autoregression model of order k, i.e., with
-            [1, y(t-1), …, y(t-k)]
-            as the t-th row of x.
-            Under the null, LM approximately has a chisquare distribution with p degrees of freedom and pval is the p-value (1 minus the CDF of this distribution at LM) of the test.
-            If no output argument is given, the p-value is displayed.
-        Calling Sequence
-            [pval, lm] = arch_test (y, x, p)
-        Parameters
-            y: Array-like. Dependent variable of the regression model.
-            x: Array-like. Independent variables of the regression model. If x is a scalar integer k, it represents the order of autoregression.
-            p : Integer. Number of lagged squared residuals to include in the heteroscedasticity model.
-        Returns:
-            pval: Float. p-value of the LM test.
-            lm: Float. Lagrange Multiplier test statistic.*/
-        Dependencies : ols, autoreg_matrix
-//helper function
+
+
 function cdf = chi2cdf ( X, n)
     df = resize_matrix ( n , size (X) , "" , n);
     [cdf,Q] = cdfchi ( "PQ" , X ,df);
 endfunction
 //main function
 function [pval, lm] = arch_test (y, x, p)
+//   Perform a Lagrange Multiplier (LM) test for conditional heteroscedasticity.
+//   Description:
+//   Perform a Lagrange Multiplier (LM) test for conditional heteroscedasticity.
+//   For a linear regression model
+//   y = x * b + e
+//   perform a Lagrange Multiplier (LM) test of the null hypothesis of no conditional heteroscedascity against the alternative of CH(p).
+//   I.e., the model is
+//   y(t) = b(1) * x(t,1) + … + b(k) * x(t,k) + e(t),
+//   given y up to t-1 and x up to t, e(t) is N(0, h(t)) with
+//   h(t) = v + a(1) * e(t-1)^2 + … + a(p) * e(t-p)^2,
+//   and the null is a(1) == … == a(p) == 0.
+//   If the second argument is a scalar integer, k, perform the same test in a linear autoregression model of order k, i.e., with
+//   [1, y(t-1), …, y(t-k)]
+//   as the t-th row of x.
+//   Under the null, LM approximately has a chisquare distribution with p degrees of freedom and pval is the p-value (1 minus the CDF of this distribution at LM) of the test.
+//   If no output argument is given, the p-value is displayed.
+// Calling Sequence
+//   [pval, lm] = arch_test (y, x, p)
+// Parameters
+//   y: Array-like. Dependent variable of the regression model.
+//   x: Array-like. Independent variables of the regression model. If x is a scalar integer k, it represents the order of autoregression.
+//   p : Integer. Number of lagged squared residuals to include in the heteroscedasticity model.
+// Returns:
+//   pval: Float. p-value of the LM test.
+//   lm: Float. Lagrange Multiplier test statistic.*/
+// Dependencies : ols, autoreg_matrix
+
   nargin = argn(2)
   if (nargin ~= 3)
     error ("arch_test: 3 input arguments required");